This paper presents an alternative energy function for Global Optimization (GO) beamforming, tailored to acoustic broadband sources. Given, that properties such as the source location, multipole rotation, or flow conditions are parameterized over the frequency, a CSM-fitting can be performed for all frequencies at once. A numerical analysis shows that the nonlinear energy function for the standard GO problem is equivalent to the source's Point Spread Function (PSF) and contains local minima at the grating- and side lobes' locations. The energy function is improved with the proposed broadband energy, as it averages the PSF. Further, it simplifies the process of identifying sources and reconstructing their spectra from the results. The paper shows that the method is superior on synthetic monopoles compared to standard GO and CLEAN-SC. For real-world data the results of the proposed method and CLEAN-SC are similar, and outperform standard GO. The main difference is that source assumption violations cause noisy maps for CLEAN-SC and cause wrong spectral estimations of the proposed method. By using reasonable initial values, the GO problem reduces to a Local Optimization problem with similar results. Further, the proposed method is able to identify synthetic multipoles with different pole amplitudes and unknown pole rotations.
翻译:本文提出了一种适用于声学宽带源的全局优化波束成形中的另一种能量函数。鉴于如源位置、多极旋转或流动条件等性质在频率上进行参数化,可以一次性为所有频率执行 CSM 拟合。数值分析表明,标准 GO 问题的非线性能量函数等同于源的点扩散函数 (PSF),并在波栅和旁瓣位置具有局部极小值。基于所提出的宽带能量,改进了能量函数,因为它平均了 PSF。此外,它简化了从结果中识别源并重建其频谱的过程。本文表明,与标准 GO 和 CLEAN-SC 相比,该方法在合成单极源的情况下优越。对于真实数据,所提出的方法和 CLEAN-SC 的结果相似,并且优于标准 GO。主要区别在于源假定违规会导致 CLEAN-SC 的嘈杂映射和所提出的方法的错误光谱估计。通过使用合理的初始值,GO 问题减少为类似的局部优化问题,并产生类似的结果。此外,该方法能够识别具有不同极幅和未知极旋转的合成多极源。